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In evolutionary linguistics, the Iterated Learning Model (ILM) is often used for simulating the first language acquisition. Our purpose in this paper is to develop an agent-based model for language contact based on ILM. We put a learning agent on each node in the social network. Our experimental result showed that the language exposure rather deteriorates the emergence of local common languages, and grammars become non-compositional, which is different from our expectation. However, we have shown that an excessive string-clipping as well as a language exposure may constrain the appearance of local language community, independent of the shape of networks., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/14225

We first show that a labelled sequent calculus G3PAL for Public AnnouncementLogic (PAL) by Maffezioli and Negri (2011) has been lacking rulesfor deriving an axiom of Hilbert-style axiomatization of PAL. Then, we provide our revised calculus GPAL to show that all the formulas provable by Hilbert-style axiomatization of PAL are also provable in GPAL together with the cut rule. We also establish that our calculus enjoys cut elimination theorem. Moreover, we show the soundness of our calculus for Kripke semantics with the notion of surviveness of possible worlds in a restricted domain. Finally, we provide a direct proof of the semantic completeness of GPAL for the link-cutting semantics of PAL., The Proceedings of the Second Taiwan Philosophical Logic Colloquium, identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/14217

When we study multi-agent communication system, it forces us to manage an existence of communication channels between agents, such as phone numbers or e-mail addresses, while ordinary modal logic for multi-agent system does not consider the notion of channel. This paper proposes a decidable and semantically complete logic of belief with communication channels, and then expands the logic with informing action operators to change agents’ beliefs via communication channels. Moreover, for a better formalism for handling these semantics efficiently, we propose a linear algebraic representation of these. That is, with the help of Fitting (2003) and van Benthem and Liu (2007), we reformulate our proposed semantics of the doxastic static logic and its dynamic extensions in terms of boolean matrices. We also implement and publicize a calculation system of our matrix reformulations as an open system on the web., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/14765

Simon Kirby claimed that human could acquire language only with learning bottoleneck, as opposed to language acquiring device (LAD) as universal grammar by Noam Chomsky, and proposed Iterated Learning Model (ILM). In that model, human infants try to find regularity in the utterances of his/her parents, and to build compositional grammar rules. Although ILM can show the development of language competency through generations, it is still hard to explain infants' phenomenal vocabulary acquisition by 18 months within a generation. It is considered that infants employ cognitive biases, which are illogical reasoning in general, to learn languages. We propose that such cognitive biases also would help to acquire syntactic rules, and thus, we implement such biases into grammar building program. As a result, we could boost the grammar acquisition in computer simulation.

This paper addresses some issues arising from theories which represent musical structure in trees. The leaves of a tree represent the notes found in the score of a piece of music, while the branches represent the manner in which these notes are an elaboration of simpler underlying structures. The idea of multi-levelled elaboration is a central feature of the Generative Theory of Tonal Music (GTTM) of Lerdahl and Jackendoff, and is found also in Schenkerian theory and some other theoretical accounts of musical structure. In previous work we have developed computable procedures for deriving these tree structures from scores, with limited success. In this paper we examine issues arising from these theories, and some of the reasons limiting our previous success. We concentrate in particular on the issue of context dependency, and consider strategies for dealing with this. We stress the need to be explicit about data structures and algorithms to derive those structures. We conjecture that an expectation-based parser with look-ahead is likely to be most successful.

This paper addresses some issues arising from theories which represent musical structure in trees. The leaves of a tree represent the notes found in the score of a piece of music, while the branches represent the manner in which these notes are an elaboration of simpler underlying structures. The idea of multi-levelled elaboration is a central feature of the Generative Theory of Tonal Music (GTTM) of Lerdahl and Jackendoff, and is found also in Schenkerian theory and some other theoretical accounts of musical structure. In previous work we have developed computable procedures for deriving these tree structures from scores, with limited success. In this paper we examine issues arising from these theories, and some of the reasons limiting our previous success. We concentrate in particular on the issue of context dependency, and consider strategies for dealing with this. We stress the need to be explicit about data structures and algorithms to derive those structures. We conjecture that an expectation-based parser with look-ahead is likely to be most successful.

Time-span tree is a stable and consistent representation of musicalstructure since most experienced listeners deliver the same one, almost independentlyfrom context and subjectivity. In this paper, we pay attention to the reductionhypothesis of the tree structure, and introduce the notion of distance asa promising candidate of stable and consistent metric of similarity. First, we designa feature structure to represent a time-span tree. Next, we regard that when abranch is removed from the tree the information corresponding to its time-span islost, and suggest that the sum of the length of those removed spans is the distancebetween two trees. We will show that the distance preserves uniqueness in multipleshortest paths, as well as the triangle inequality. Thereafter, we illustrate howthe distance works as a metric of similarity, and then, we discuss the feasibilityand the problem of our methodology., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/10933

Up to now, experiments run with many subjects are almost the only way for demonstrating the validity of a musical algorithm. In contrast, we employ formalism to verify that a melodic morphing algorithm correctly works as specified. The way we present in the paper is formal, theoretical, and viable. We provide a full-fledged feature structure for representing a time-span tree of ``A Generative Theory of Tonal Music'' (GTTM). The key idea here is that the GTTM reduction is identified with the subsumption or the ``is-a'' relation, which is the most fundamental relation in knowledge representation. Since we obtain the domain in which a partial order is defined, we introduce the join and meet operations based on unification. In such an algebraic framework, as preliminaries of the proof of a melodic morphing algorithm, we introduce the following notions: reduction path, melodic complexity, similarity, and interpolation. These notions are defined using the subsumption relation, join and meet, in a formal way. Thenwe take the melodic morphing algorithm proposed by Hamanaka et al. (2008) because it is constructed using the join and meet operations. Finally we prove the theorem that the melodies generated by the algorithm are the interpolations of two given melodies.

It is well known that the symmetry bias greatly accelerates vocabulary learning. In particular, the bias helps infants to connect objects with their names easily. However, grammar learning is another important aspect of language acquisition. In this study, we propose that the symmetry bias also helps to acquire grammar rules faster. We employ the Iterated Learning Model, and revise it to include the symmetry bias. The result of the simulations shows that infants could abduce the meanings from unrecognized utterances using the symmetry bias, and acquire compositional grammar from a reduced amount of learning data., Special Issue: 3rd International Conference on Language and Automata Theory and Applications (LATA 2009), identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/9823

Creolization is a self-organization process of new language community. Thus far, a simulation study of the emergence of creoles has been reported in the mathematical framework. In this paper we introduce a spatial structure to the framework. We show that local creole communities are organized, and creolization may occur when language learners learn often from non-parental language speakers, in contrast to the non-spatial model., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/8478

The purpose of this paper is to develop a new formalism of language dynamics so that creole may emerge. Thus far, we modified the transition probability of the dynamics so as to change in accordance with the distribution of population of each language at each generation, and in addition, we introduced a new parameter called exposure rate with which infants were exposed to other languages than mother tongues. Thus, we could observe creolization under limited conditions. In this paper, we revise the learning algorithm in our model, considering the amount of language input during the language acquisition period. Thus, the transition probability depends not only on the exposure rate but also on the amount of language input. With this model, we show that creolization occurs only when the influence of mother tongues and the socially dominant languages balance., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/7878

Language change is considered as a transition of a user population among languages. Language dynamics equations represent such a transition of population. Our purpose in this paper is to develop a new formalism of language dynamics based on a realistic situation of multiple language contact. We assume a situation where memoryless learners are exposed to a number of languages. Our experiments show that contact with other language speakers during the acquisition of a first language reduces learning accuracy and prevents the emergence of a dominant language. We suppose there is a special communicative language which has a higher similarity to some languages than others; when learners are frequently exposed to a variety of languages, these similar languages attract a relatively higher proportion of the population. We discuss the simulation results from the viewpoint of the language bioprogram hypothesis., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/7922